It is often important to detect sites where mutations have been driven to fixation by positive selection, or which are constrained by purifying selection. Underlying such selective pressures are the physico-chemical differences (e.g. in hydropathy, polarity or volume) between different amino acids. Even when some amino acid changes at a site are favored by positive selection (e.g. because substituting an amino acid with different polarity may be favorable), selective constraints can still be expected to suppress other changes at the same site (e.g. because an amino acid with different volume would disrupt the folding of the protein). Thus different selective pressure can act on different properties at the same site. Moreover, a physico-chemical property that is important to conserve at one site may be unimportant at another. In this project we will use our expertise in computational and statistical modeling of evolution and selection to develop computational and statistical methodology to elucidate which physico-chemical properties are important at which sites. Our methods will identify not only functionally important sites experiencing selection, but the physico-chemical constraints under which evolution operates at those sites and the selective pressure causing some physico-chemical properties to change adaptively. We will use these methods to study the biochemical basis of adaptation in several biomedically important contexts, including immune escape and reversion in viral pathogens, viral transmission, and viral adaptation to different host compartments.